Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

21 October 2019

Eyke Hüllermeier

Papers citing "Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods"

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Correcting Annotator Bias in Training Data: Population-Aligned Instance Replication (PAIR) Stephanie Eckman Bolei Ma Christoph Kern Rob Chew Barbara Plank Frauke Kreuter 41 0 0 12 Jan 2025
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials Matthias Holzenkamp Dongyu Lyu Ulrich Kleinekathöfer Peter Zaspel 33 0 0 10 Jan 2025
AdaPRL: Adaptive Pairwise Regression Learning with Uncertainty Estimation for Universal Regression Tasks Fuhang Liang Rucong Xu Deng Lin OOD 33 0 0 10 Jan 2025
Predictable Artificial Intelligence Lexin Zhou Pablo Antonio Moreno Casares Fernando Martínez-Plumed John Burden Ryan Burnell ... Seán Ó hÉigeartaigh Danaja Rutar Wout Schellaert Konstantinos Voudouris José Hernández Orallo 51 2 0 08 Jan 2025
Partial-Label Learning with a Reject Option Tobias Fuchs Florian Kalinke Klemens Bohm 40 0 0 08 Jan 2025
Uncertainty separation via ensemble quantile regression Navid Ansari Hans-Peter Seidel Vahid Babaei UD UQCV 74 0 0 18 Dec 2024
Optical aberrations in autonomous driving: Physics-informed parameterized temperature scaling for neural network uncertainty calibration D. Wolf Alexander Braun Markus Ulrich 89 0 0 18 Dec 2024
Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Martin Aubard Ana Madureira Luis F. Teixeira José Pinto AAML 73 2 0 16 Dec 2024
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haochen Shi Yibin Wang Ligong Han H. M. Zhang Hao Wang UQCV 83 0 0 07 Dec 2024
Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation Gianni Franchi Dat Nguyen Trong Nacim Belkhir Guoxuan Xia Andrea Pilzer UQLM 78 0 0 04 Dec 2024
Divergent Ensemble Networks: Enhancing Uncertainty Estimation with Shared Representations and Independent Branching Arnav Kharbanda Advait Chandorkar UQCV 67 0 0 02 Dec 2024
Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Control Negin Amirshirzad Mehmet Arda Eren Erhan Oztop 62 0 0 30 Nov 2024
Uni-SLAM: Uncertainty-Aware Neural Implicit SLAM for Real-Time Dense Indoor Scene Reconstruction Shaoxiang Wang Yaxu Xie Chun-Peng Chang Christen Millerdurai A. Pagani Didier Stricker 67 1 0 29 Nov 2024
Exploring Aleatoric Uncertainty in Object Detection via Vision Foundation Models Peng Cui Guande He Dan Zhang Zhijie Deng Yinpeng Dong Jun Zhu 82 0 0 26 Nov 2024
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 91 1 0 25 Nov 2024
Fine-Grained Uncertainty Quantification via Collisions Jesse Friedbaum S. Adiga Ravi Tandon 69 0 0 18 Nov 2024
Conformalized Credal Regions for Classification with Ambiguous Ground Truth Michele Caprio David Stutz Shuo Li Arnaud Doucet UQCV 64 4 0 07 Nov 2024
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 54 2 0 05 Nov 2024
Uncertainty measurement for complex event prediction in safety-critical systems Maria J. P. Peixoto Akramul Azim 26 0 0 02 Nov 2024
State- and context-dependent robotic manipulation and grasping via uncertainty-aware imitation learning Tim R. Winter Ashok M. Sundaram W. Friedl Máximo A. Roa F. Stulp João Silvério 31 0 0 31 Oct 2024
On the Robustness of Adversarial Training Against Uncertainty Attacks Emanuele Ledda Giovanni Scodeller Daniele Angioni Giorgio Piras Antonio Emanuele Cinà Giorgio Fumera Battista Biggio Fabio Roli AAML 30 1 0 29 Oct 2024
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models Tuwe Löfström Fatima Rabia Yapicioglu Alessandra Stramiglio Helena Lofstrom Fabio Vitali FAtt LRM 44 0 0 28 Oct 2024
Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models Mohammad Beigi Sijia Wang Ying Shen Zihao Lin Adithya Kulkarni ... Ming Jin Jin-Hee Cho Dawei Zhou Chang-Tien Lu Lifu Huang 29 1 0 26 Oct 2024
Can Uncertainty Quantification Enable Better Learning-based Index Tuning? Tao Yu Zhaonian Zou Hao Xiong 16 1 0 23 Oct 2024
Mislabeled examples detection viewed as probing machine learning models: concepts, survey and extensive benchmark Thomas George Pierre Nodet A. Bondu Vincent Lemaire VLM 32 0 0 21 Oct 2024
A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice Hsiu-Yuan Huang Yutong Yang Zhaoxi Zhang Sanwoo Lee Yunfang Wu 36 9 0 20 Oct 2024
Accounting for Sycophancy in Language Model Uncertainty Estimation Anthony Sicilia Mert Inan Malihe Alikhani 24 1 0 17 Oct 2024
Principled Bayesian Optimisation in Collaboration with Human Experts Wenjie Xu Masaki Adachi Colin N. Jones Michael A. Osborne 33 2 0 14 Oct 2024
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization Johan Hatleskog Kostas Alexis 3DPC 44 2 0 14 Oct 2024
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation Hanieh Shojaei Qianqian Zou Max Mehltretter UQCV 16 0 0 11 Oct 2024
Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble Deep Kernel Learning Model Yonghang Zhou Hongyi Zhu Yidong Chai Yuanchun Jiang Yezheng Liu AAML 24 0 0 10 Oct 2024
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs Ruijia Niu D. Wu Rose Yu Yi-An Ma 33 1 0 09 Oct 2024
Uncertainty estimation via ensembles of deep learning models and dropout layers for seismic traces Giovanni Messuti ortensia Amoroso Ferdinando Napolitano Mariarosaria Falanga Paolo Capuano Silvia Scarpetta UQCV 18 0 0 08 Oct 2024
Active Evaluation Acquisition for Efficient LLM Benchmarking Yang Li Jie Ma Miguel Ballesteros Yassine Benajiba Graham Horwood ELM 29 1 0 08 Oct 2024
Ensured: Explanations for Decreasing the Epistemic Uncertainty in Predictions Helena Lofstrom Tuwe Löfström Johan Hallberg Szabadvary 33 0 0 07 Oct 2024
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning Nils Lehmann Jakob Gawlikowski Adam J. Stewart Vytautas Jancauskas Stefan Depeweg Eric T. Nalisnick N. Gottschling 42 0 0 04 Oct 2024
FairlyUncertain: A Comprehensive Benchmark of Uncertainty in Algorithmic Fairness Lucas Rosenblatt R. T. Witter FaML 22 0 0 02 Oct 2024
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks M. Haywood-Alexander Giacamo Arcieri A. Kamariotis Eleni Chatzi 34 1 0 02 Oct 2024
Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown Xingzhou Lou Dong Yan Wei Shen Yuzi Yan Jian Xie Junge Zhang 45 22 0 01 Oct 2024
Bridging the Gap in Hybrid Decision-Making Systems Federico Mazzoni Roberto Pellungrini Riccardo Guidotti 31 0 0 28 Sep 2024
ReliOcc: Towards Reliable Semantic Occupancy Prediction via Uncertainty Learning Song Wang Zhongdao Wang Jiawei Yu Wentong Li Bailan Feng Junbo Chen Jianke Zhu UQCV 34 3 0 26 Sep 2024
Scalable Ensemble Diversification for OOD Generalization and Detection Alexander Rubinstein Luca Scimeca Damien Teney Seong Joon Oh BDL OOD 355 1 0 25 Sep 2024
An Efficient Model-Agnostic Approach for Uncertainty Estimation in Data-Restricted Pedometric Applications Viacheslav Barkov Jonas Schmidinger Robin Gebbers Martin Atzmueller 28 1 0 18 Sep 2024
Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks Edgar Heinert Stephan Tilgner Timo Palm Matthias Rottmann UQCV 43 0 0 17 Sep 2024
Quantile Regression for Distributional Reward Models in RLHF Nicolai Dorka 32 16 0 16 Sep 2024
Confidence Estimation for LLM-Based Dialogue State Tracking Yi-Jyun Sun Suvodip Dey Dilek Z. Hakkani-Tür Gökhan Tür 48 1 0 15 Sep 2024
Uncertainty and Generalizability in Foundation Models for Earth Observation Raúl Ramos-Pollán F. Kalaitzis Karthick Panner Selvam 34 0 0 13 Sep 2024
DEMAU: Decompose, Explore, Model and Analyse Uncertainties A. Hoarau Vincent Lemaire UQCV UD PER 31 0 0 12 Sep 2024
Empowering Bayesian Neural Networks with Functional Priors through Anchored Ensembling for Mechanics Surrogate Modeling Applications Javad Ghorbanian Nicholas Casaprima Audrey Olivier 28 0 0 08 Sep 2024
Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression Labels Emma Svensson Hannah Rosa Friesacher S. Winiwarter Lewis H. Mervin Adam Arany O. Engkvist 42 2 0 06 Sep 2024